计算机科学与探索 ›› 2019, Vol. 13 ›› Issue (1): 70-82.DOI: 10.3778/j.issn.1673-9418.1710049

• 网络与信息安全 • 上一篇    下一篇

PLRD-(k,m):保护链接关系的分布式k-度-m-标签匿名方法

张晓琳,何晓玉+,张换香,李卓麟   

  1. 内蒙古科技大学 信息工程学院,内蒙古 包头 014010
  • 出版日期:2019-01-01 发布日期:2019-01-09

PLRD-(k,m):Distributed k-Degree-m-Label Anonymity with Protecting Link Rela-tionships

ZHANG Xiaolin, HE Xiaoyu+, ZHANG Huanxiang, LI Zhuolin   

  1. School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia 014010, China
  • Online:2019-01-01 Published:2019-01-09

摘要: 现有的匿名技术多关注匿名后数据的可用性,忽略了攻击者可以通过多种背景知识进行攻击的问题。此外,随着用户规模的逐年递增,传统的匿名技术已不能满足实际需求。为此,提出一种保护链接关系的分布式匿名方法PLRD-(k,m)(distributed k-degree-m-label anonymity with protecting link relationships)。该方法利用GraphX的消息传递机制,通过将互为N-hop邻居的节点分为一组并进行k-degree匿名和m-标签匿名,保证攻击者无法通过度和标签识别出目标并保护链接关系不被泄露。最后,扩展了PLRD-(k,m)方法,提出一种个性化匿名方法以满足用户不同的需求。基于真实社会网络数据集的实验结果表明,提出的方法不仅能提高处理大规模社会网络的执行效率,同时具有很好的数据可用性。

关键词: 社会网络, 隐私保护, 分布式, k-度-m-标签匿名, GraphX

Abstract: Existing anonymous technologies pay more attention to the utility of anonymous data, ignoring the problem that attackers recognize targets through a variety of background knowledge. In addition, with the scale of users increasing year by year, the traditional anonymous technologies can??t meet the actual demand. Motivated by this, a distributed k-degree-m-label anonymity method with protecting link relationships (called PLRD-(k, m)) is proposed. This method utilizes the message passing mechanism of GraphX, and divides nodes that are N-hop neighbors into one group and performs k-degree anonymous and m-label anonymous to ensure that attackers can??t identify targets by degrees and labels, and protects link relationships from being leaked. Finally, a protecting link relationships distributed personalized anonymity method extended from PLRD-(k, m) is proposed. Experimental results based on real social network datasets show that the proposed method can not only improve the execution efficiency of large-scale social networks, but also has good data utility.

Key words: social network, privacy preserving, distributed, k-degree-m-label anonymity, GraphX